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ild_power() for
simulation-based power of a fixed effect (ild_simulate -> ild_lme
-> Wald rejection). Uses small n_sim in examples; lmerMod inference
via Wald z-approximation when p-values not from backend.ild_design_check() aggregates spacing, WP/BP decomposition,
missingness; ild_spacing() reports interval stats and
AR1/CAR1 recommendation; ild_missing_bias() tests
informative missingness; ild_center_plot() for WP/BP
density plot.ild_crosslag() (ild_lag + ild_check_lags + ild_lme);
ild_person_model() and
ild_person_distribution() for per-person fits and estimate
distribution.ild_heatmap(),
ild_spaghetti() (aliases); ild_circadian() for
time-of-day; ild_align() for multi-stream alignment within
a time window.augment_ild_model(),
tidy_ild_model() with consistent columns across lmer/nlme;
S3 print methods for diagnostics and tidy model.set.seed() for determinism; ild_power examples kept small
(n_sim = 25).ild_prepare(), ild_summary(),
ild_center(), ild_lag() (index, gap-aware,
time-window), ild_spacing_class(),
ild_missing_pattern(), ild_check_lags().ild_lme() (lmer or nlme with AR1/CAR1),
ild_diagnostics(), ild_plot() (trajectory,
gaps, missingness, fitted, residual ACF).ild_simulate(), ild_manifest()
/ ild_bundle() for reproducibility, broom integration for
ild_lme fits.ema_example dataset.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.